Real Estate Pricing

Deep dive into real estate pricing key factors and predict residential real estate prices at individual and portfolio levels using an easily customizable project.

The goal of this adapt and apply solution is to show asset management organizations how Dataiku can be used to predict the price of residential real estate using publicly available data in order to identify key factors in real estate pricing at individual and portfolio levels.  More details on the specifics of the solution can be found on the knowledge base. This solution is only available on installed instances.

Business Overview

Assets invested in Real Estate have x3 in the past ten years to exceed 3,3 trn$ AUM. The pandemic has triggered significant volatility on real estate pricing: on average, commercial real estate indexes have seen their prices drop by -25% in a year.

In this non-regulated market, the importance of strong valuation strategies is critical to support opportunity identification, fuel impactful negotiation strategies, and optimize P&L management. Teams focused on developing effective valuation models need to manage complex data integrations, detailed modelling challenges, while ensuring the output results are easily consumable by other teams and clients.

This work can often involve distinct skillsets and underlying technologies, making collaboration challenging and creating project inefficiencies. By removing the need for upfront investment in Webapp and API design,  allowing data scientists, data analysts and asset managers to interact collaboratively, and providing a flexible and complete project framework with real-world data, this solution accelerates time to insight and minimizes unnecessary development and effort.


  • Zoom into specific insights for each input dataset through easily configurable dashboards.
  • Predict real estate purchase prices thanks to a machine-learning powered model.
  • Ensure highest level of understanding and transparency on model features and input data sources.
  • Access predicted valuations in whatever way is of most value: interactive Webapp, API calls, or bulk export.
  • Easily adapt the pricing engine to different regions, types of assets and enrich with additional data inputs.